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The era of genome-wide association studies (GWAS) has led to the discovery of numerous genetic variants associated with disease. Better understanding of whether these or other variants interact leading to differential risk compared with individual marker effects will increase our understanding of the genetic architecture of disease, which may be investigated using the family-based study design. We present M-TDT (the multi-locus transmission disequilibrium test), a tool for detecting family-based multi-locus multi-allelic effects for qualitative or quantitative traits, extended from the original transmission disequilibrium test (TDT). Tests to handle the comparison between additive and epistatic models, lack of independence between markers and multiple offspring are described. Performance of M-TDT is compared with a multifactor dimensionality reduction (MDR) approach designed for investigating families in the hypothesis-free genome-wide setting (the multifactor dimensionality reduction pedigree disequilibrium test, MDR-PDT). Other methods derived from the TDT or MDR to investigate genetic interaction in the family-based design are also discussed. The case of three independent biallelic loci is illustrated using simulations for one- to three-locus alternative hypotheses. M-TDT identified joint-locus effects and distinguished effectively between additive and epistatic models. We showed a practical example of M-TDT based on three genes already known to be implicated in malaria susceptibility. Our findings demonstrate the value of M-TDT in a hypothesis-driven context to test for multi-way epistasis underlying common disease etiology, whereas MDR-PDT-based methods are more appropriate in a hypothesis-free genome-wide setting. [ABSTRACT FROM AUTHOR]

Background: Despite significant progress in malaria control over the past twenty years, malaria remains a leading cause of child morbidity and mortality in Tropical Africa. As most patients do not consult any health facility much uncertainty persists about the true burden of the disease and the range of individual differences in susceptibility to malaria., Methods: Over a 25-years period, from 1990 to 2015, the inhabitants of Dielmo village, Senegal, an area of intense malaria transmission, have been monitored daily for their presence in the village and the occurrence of diseases. In case of fever thick blood films were systematically examined through microscopy for malaria parasites and patients received prompt diagnosis and treatment., Findings: We analysed data collected in 111 children and young adults monitored for at least 10 years (mean 17.3 years, maximum 25 years) enrolled either at birth (95 persons) or during the two first years of life. A total of 11,599 episodes of fever were documented, including 5268 malaria attacks. The maximum number of malaria attacks in a single person was 112. Three other persons suffered one hundred or more malaria attacks during follow-up. The minimum number of malaria attacks in a single person was 11. The mean numbers of malaria attacks in children reaching their 4th, 7th, and 10th birthdays were 23.0, 37.7, and 43.6 attacks since birth, respectively. Sixteen children (14.4%) suffered ten or more malaria attacks each year at ages 1-3 years, and six children (5.4%) each year at age 4-6 years., Interpretation: Long-term close monitoring shows that in highly endemic areas the malaria burden is higher than expected. Susceptibility to the disease may vary up to 10-fold, and for most children childhood is an endless history of malaria fever episodes. No other parasitic, bacterial or viral infection in human populations has such an impact on health., Funding: The Pasteur Institutes of Dakar and Paris, the Institut de Recherche pour le Développement, and the French Ministry of Cooperation provided funding., Competing Interests: We declare that we have no conflict of interest., (© 2023 The Author(s).)

Background: The novel coronavirus disease 2019 (COVID-19) pandemic has spread from China to the rest of the world. Africa seems less impacted with lower number of cases and deaths than other continents. Senegal recorded its first case on March 2, 2020. We present here data collected from March 2 to October 31, 2020 in Senegal., Methods: Socio-demographic, epidemiological, clinical and virological information were collected on suspected cases. To determine factors associated with diagnosed infection, symptomatic disease and death, multivariable binary logistic regression and log binomial models were used. Epidemiological parameters such as the reproduction number and growth rate were estimated., Results: 67,608 suspected cases were tested by the IPD laboratories (13,031 positive and 54,577 negative). All age categories were associated with SARS-CoV-2 infection, but also patients having diabetes or hypertension or other cardiovascular diseases. With diagnosed infection, patients over 65 years and those with hypertension and cardiovascular disease and diabetes were highly associated with death. Patients with co-morbidities were associated with symptomatic disease, but only the under 15 years were not associated with. Among infected, 27.67% were asymptomatic (40.9% when contacts were systematically tested; 12.11% when only symptomatic or high-risk contacts were tested). Less than 15 years-old were mostly asymptomatic (63.2%). Dakar accounted for 81.4% of confirmed cases. The estimated mean serial interval was 5.57 (± 5.14) days. The average reproduction number was estimated at 1.161 (95%CI: 1.159-1.162), the growth rate was 0.031 (95%CI: 0.028-0.034) per day., Conclusions: Our findings indicated that factors associated with symptomatic COVID-19 and death are advanced age (over 65 years-old) and comorbidities such as diabetes and hypertension and cardiovascular disease., Competing Interests: The authors have declared that no competing interests exist.

Background: When vaccines against the novel COVID-19 were available in Senegal, many questions were raised. How long should non-pharmaceutical interventions (NPIs) be maintained during vaccination roll-out? What are the best vaccination strategies?, Methods: In this study, we used an age-structured dynamic mathematical model. This model uses parameters based on SARS-CoV-2 virus, information on different types of NPIs, epidemiological and demographic data, some parameters relating to hospitalisations and vaccination in Senegal., Results: In all scenarios explored, the model predicts a larger third epidemic wave of COVID-19 in terms of new cases and deaths than the previous waves. In a context of limited vaccine supply, vaccination alone will not be sufficient to control the epidemic, and the continuation of NPIs is necessary to flatten the epidemic curve. Assuming 20% of the population have been vaccinated, the optimal period to relax NPIs would be a few days from the last peak. Regarding the prioritisation of age groups to be vaccinated, the model shows that it is better to vaccinate individuals aged 5-60 years and not just the elderly (over 60 years) and those in high-risk groups. This strategy could be more cost-effective for the government, as it would reduce the high costs associated with hospitalisation. In terms of vaccine distribution, the optimal strategy would be to allocate full dose to the elderly. If vaccine doses are limited, half dose followed by full dose would be sufficient for people under 40 years because whether they receive half or full dose, the reduction in hospitalisations would be similar and their death-to-case ratio is very low., Conclusions: This study could be presented as a decision support tool to help devise strategies to control the COVID-19 pandemic and help the Ministry of Health to better manage and allocate the available vaccine doses., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)